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Catalogs from Multiwavelength data Mario Nonino (OATS-INAF)

Catalogs from Multiwavelength data Mario Nonino (OATS-INAF). Outline. Motivation Methods Applications Example. Background. Study the formation and evolution of galaxies through the analysis of Luminosity, Mass functions and clustering properties.

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Catalogs from Multiwavelength data Mario Nonino (OATS-INAF)

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  1. CatalogsfromMultiwavelength dataMario Nonino (OATS-INAF)

  2. Outline • Motivation • Methods • Applications • Example

  3. Background • Study the formation and evolution of galaxies through the analysis of Luminosity, Mass functions and clustering properties. • The formation, evolution and role of AGNs. • What has been the star formation history of different galaxy types. • What role does environment (field, groups, clusters) play? • How did galaxies acquire their diversity of morphology?

  4. Background 2 • Issues are addressed via multiwavelength obs. campaigns: from x-ray (CXO, XMM) to UV (Galex), Optical & Nir (ground and space based), Mid and Far Infrared (ISO, Spitzer) up to mm and radio wavelengths (VLA) . • Examples: GOODS, COSMOS.

  5. Background 3 • GOODS in short: • Started as Chandra Deep Field South (1999) : one of the two deepest x-ray observations aiming at resolving the x-ray background. • One of the two fields targeted (+HDFN) for deep imaging with HST+ACS, and Spitzer. • Observed with a large variety of telescopes • ESO support: ~250 nights on GOODS-South

  6. Multiwavelength catalog: what is it ? • Assume we have observations of the same patch in the sky obtained with different telescopes and filters. • What are the assumptions behind? Same position == same object. (not to mention time variability) • Multiwavelength data: the same source as seen in different bands.

  7. Multiwavelength catalog: how to create it • Same position: the input images need to be astrometrically well calibrated. • Sources are detected in all images separately, and then catalogs are matched and merged. • But what about sources not detected in different bands? Example drop-outs

  8. Multiwavelength catalog: how to create it image=sources+noise • Connoly, Szalay & Szokoly (1999): transform each image into a normal gaussian (0 mean and unit variance) • With n input images you get: Simpler approach: select one band, usually a red one for the detection and all the others for measure only.

  9. Multiwavelength catalog: generation • A common requirement for these steps is that the PSF effects should be taken into account! • I=TP+N : the observed image (I) is the convolution of the true image(T) with the PSF (P) plus the noise (N) • Different instruments/observing conditions result in different PSF

  10. Multiwavelength catalog: generation • Let A the image chosen to be the reference. B is another image with a different PSF with respect to A. • Then: psf_A= psf_B  Kernel , which in Fourier space becomes : FFT(psf_A)=FFT(psf_B) * FFT(K) • Matched_B = FFT^-1 (FFT(Original_B) * FFT(K)) • High frequency components need to be smoothed (they are dominated by the noise). • One of the main cons of this approach is that objects tend to be blended since most of the time A is the worst PSF image.

  11. Aperture mag • Quick solution (but only for faint objects…)

  12. Completeness

  13. Magnitude • Which magnitude is to be used? • The easy way: aperture magnitude • Kron magnitude • Petrosian magnitude (Ap.J., 209,1976,L1-L5)

  14. Magnitude: system • From raw counts to magnitude • The AB system: m(AB)= -2.5 log(f) – 48.60 (48.57) when f is measured in erg s^-1 cm^-2 Hz^-1 • The advantage of AB system is that magnitudes are directly related to physical units:

  15. Mass estimation (e.g. Bruzual & Charlot,MNRAS, 2003,344)

  16. Drop outs : to high-z

  17. Using multicolor cat. for drop out search • Color-color plots

  18. Photometric redshift: when spectroscopy is not enough

  19. Photometric redshift: when spectroscopy is not enough

  20. Very distant galaxy (candidate...)

  21. A really short introduction to sextractor(e.g. http://www-int.stsci.edu/~holwerda/OldHomepage/se.htmland the program manual)

  22. How to run it: now the practical session... • sex -c <config_file> <input_image> -PARAMETER parameter_value • Remember to change: CATALOG_NAME, MAG_ZEROPOINT ! • The zeropoints to be used are: • U: 33.53 • R: 34.05 • z (F850LP) : 24.84 • Ks: 26.0 • IRAC: 22.42 • To extract a meaningful catalog, remember to exclude the regions NOT in common in all bands. A quick way to do this is: display all images, taken note of the minimum and maximum good values for x and y. Then just type : cat your_catalog_name | awk ' {if ($4 > xmin && $4 < xmax && $5 > ymin && $5 < ymax) print $0}' > sub_catalog_name. • To paste all catalogs together: paste cat1 cat2 cat3 .. > colour.cat

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